Xiaofeng Yang – författare

Image synthesis across and within medical imaging modalities is an active area of research with broad applications in radiology and radiation oncology. This book covers the principles and methods of medical image synthesis, along with state-of-the-art research.

First, various traditional non-learning-based, traditional machine-learning-based, and recent deep-learning-based medical image synthesis methods are reviewed. Second, specific applications of different inter- and intra-modality image synthesis tasks and of synthetic image-aided segmentation and registration are introduced and summarized, listing and highlighting the proposed methods, study designs, and reported performances with the related clinical applications of representative studies. Third, the clinical usages of medical image synthesis, such as treatment planning and image-guided adaptive radiotherapy, are discussed. Last, the limitations and current challenges of various medical synthesis applications are explored, along with future trends and potential solutions to solve these difficulties.

The benefits of medical image synthesis have sparked growing interest in a number of advanced clinical applications, such as magnetic resonance imaging (MRI)-only radiation therapy treatment planning and positron emission tomography (PET)/MRI scanning. This book will be a comprehensive and exciting resource for undergraduates, graduates, researchers, and practitioners.

Image synthesis across and within medical imaging modalities is an active area of research with broad applications in radiology and radiation oncology. This book covers the principles and methods of medical image synthesis, along with state-of-the-art research.

First, various traditional non-learning-based, traditional machine-learning-based, and recent deep-learning-based medical image synthesis methods are reviewed. Second, specific applications of different inter- and intra-modality image synthesis tasks and of synthetic image-aided segmentation and registration are introduced and summarized, listing and highlighting the proposed methods, study designs, and reported performances with the related clinical applications of representative studies. Third, the clinical usages of medical image synthesis, such as treatment planning and image-guided adaptive radiotherapy, are discussed. Last, the limitations and current challenges of various medical synthesis applications are explored, along with future trends and potential solutions to solve these difficulties.

The benefits of medical image synthesis have sparked growing interest in a number of advanced clinical applications, such as magnetic resonance imaging (MRI)-only radiation therapy treatment planning and positron emission tomography (PET)/MRI scanning. This book will be a comprehensive and exciting resource for undergraduates, graduates, researchers, and practitioners.

AI-driven Medical Image Analysis in Precision Radiation Therapy provides a comprehensive overview of the latest developments in artificial intelligence for medical imaging, focusing on applications in precision radiation therapy. Written by a team of experts, it offers an accessible perspective on how AI is transforming cancer treatment for a broad audience, from computer science and engineering to the medical sector. The text covers key techniques such as image synthesis, segmentation, and registration, but its primary focus is on practical clinical applications. It showcases recent studies in image-guided and adaptive radiation therapy, real-time tumor motion tracking, and treatment response assessment for both photon and proton therapies. Furthermore, the book addresses the real-world challenges of implementing these AI techniques in a clinical setting, equipping readers with the practical knowledge needed for successful integration. It is an essential guide for students and newcomers, as well as a valuable reference for experienced medical physicists and radiation oncologists.

Key Features:

AI-driven Medical Image Analysis in Precision Radiation Therapy provides a comprehensive overview of the latest developments in artificial intelligence for medical imaging, focusing on applications in precision radiation therapy. Written by a team of experts, it offers an accessible perspective on how AI is transforming cancer treatment for a broad audience, from computer science and engineering to the medical sector. The text covers key techniques such as image synthesis, segmentation, and registration, but its primary focus is on practical clinical applications. It showcases recent studies in image-guided and adaptive radiation therapy, real-time tumor motion tracking, and treatment response assessment for both photon and proton therapies. Furthermore, the book addresses the real-world challenges of implementing these AI techniques in a clinical setting, equipping readers with the practical knowledge needed for successful integration. It is an essential guide for students and newcomers, as well as a valuable reference for experienced medical physicists and radiation oncologists.

Key Features:

A guide to the wide-variety of waste valorisation techniques related to various biomass, waste materials and by products

Waste Valorisation provides a comprehensive review of waste chemistry and its application to the generation of value-added products. The authors – noted experts on the topic – offer a clear understanding of waste diversity, drivers and policies governing its valorisation based on the location. The book provides information on the principles behind various valorisation schemes and offers a description of general treatment options with their evaluation guidelines in terms of cost, energy consumption and waste generation.

Each of the book''s chapters contain an introduction which summarises the current production and processing methods, yields, energy sources and other pertinent information for each specific type of waste. The authors focus on the most relevant novel technologies for value-added processing of waste streams or industrial by-products which can readily be integrated into current waste management systems. They also provide the pertinent technical, economic, social and environmental evaluations of bioconversions as future sustainable technologies in a biorefinery. This important book:

Written for academic researchers and industrial scientists working in agricultural and food production, bioconversions and waste management professionals, Waste Valorisation is an authoritative guide to the chemistry and applications of waste materials and provides an overview of the most recent developments in the field.

A guide to the wide-variety of waste valorisation techniques related to various biomass, waste materials and by products

Waste Valorisation provides a comprehensive review of waste chemistry and its application to the generation of value-added products. The authors – noted experts on the topic – offer a clear understanding of waste diversity, drivers and policies governing its valorisation based on the location. The book provides information on the principles behind various valorisation schemes and offers a description of general treatment options with their evaluation guidelines in terms of cost, energy consumption and waste generation.

Each of the book''s chapters contain an introduction which summarises the current production and processing methods, yields, energy sources and other pertinent information for each specific type of waste. The authors focus on the most relevant novel technologies for value-added processing of waste streams or industrial by-products which can readily be integrated into current waste management systems. They also provide the pertinent technical, economic, social and environmental evaluations of bioconversions as future sustainable technologies in a biorefinery. This important book:

Written for academic researchers and industrial scientists working in agricultural and food production, bioconversions and waste management professionals, Waste Valorisation is an authoritative guide to the chemistry and applications of waste materials and provides an overview of the most recent developments in the field.

The oceans cover approximately 71% of Earth’s surface, 90% of the biosphere and contains 97% of Earth’s water. Since the first launch of SEASAT satellite in 1978, an increasing number of SAR satellites have or will become available, such as the European Space Agency’s ERS-1/-2, ENVISAT, and Sentinel-1 series; the Canadian RADARSAT-1/-2 and the upcoming RADARSAT Constellation Mission series satellites; the Italian COSMO-SkyMed satellites, the German TERRASAR-X and TANDEM-X, and the Chinese GAOFEN-3 SAR, among others. Recently, European Space Agency has launched a new generation of SAR satellites, Sentinel-1A in 2014 and Sentinel-1B in 2016. These SAR satellites provide researchers with free and open SAR images necessary to carry out their research on the global oceans. The scope of Advances in SAR Remote Sensing of Oceans is to demonstrate the types of information that can be obtained from SAR images of the oceans, and the cutting-edge methods needed for analysing SAR images.

Written by leading experts in the field, and divided into four sections, the book presents the basic principles of radar backscattering from the ocean surface; introduces the recent progresses in SAR remote sensing of dynamic coastal environment and management; discusses the state-of-the-art methods to monitor parameters or phenomena related to the dynamic ocean environment; and deals specifically with new techniques and findings of marine atmospheric boundary layer observations.

Advances in SAR Remote Sensing of Oceans is a very comprehensive and up-to-date reference intended for use by graduate students, researchers, practitioners, and R&D engineers working in the vibrant field of oceans, interested to understand how SAR remote sensing can support oceanography research and applications.